Refactor test UDAF registration by removing unused accumulator code

Author: kosiew

examples/datafusion-ffi-example/python/tests/_test_type_checking.py

@@ -1,40 +1,4 @@
-import pyarrow as pa
-from datafusion import udaf, SessionContext
-from datafusion.user_defined import Accumulator  # base class for aggregators
-
-# Define a simple test accumulator for demonstration:
-class TestAccumulator(Accumulator):
-    def __init__(self) -> None:
-        self.total = 0
-
-    def state(self) -> list[pa.Scalar]:
-        return [pa.scalar(self.total)]
-
-    def update(self, *values: pa.Array) -> None:
-        # Sum up integer values from the first argument
-        self.total += sum(value.as_py() for value in values[0])
-
-    def merge(self, states: list[pa.Array]) -> None:
-        # Assumes the state is a list with one scalar integer per actor
-        self.total += sum(state[0].as_py() for state in states)
-
-    def evaluate(self) -> pa.Scalar:
-        return pa.scalar(self.total)
-
-# Create the test UDAF using TestAccumulator.
-# Note: the overload taking (accum, input_types, return_type, state_type, volatility, name)
-test_udaf = udaf(
-    TestAccumulator,           # accumulator function or type producing an Accumulator object
-    [pa.int64()],              # input types (list of one int64)
-    pa.int64(),                # return type
-    [pa.int64()],              # state type (list of one int64)
-    "immutable",               # volatility indicator
-    name="test_udaf"
-)
-
-# Register UDAF into a session context (if needed)
+from datafusion import SessionContext, udf, udaf
+from geodatafusion import native
 ctx = SessionContext()
-ctx.register_udaf(test_udaf)
-
-# The code should type check without error:
-print("Type checking passed for test_udaf!")
+ctx.register_udaf(udaf(native.Extent()))